alexa Derivation of the SLEDAI. A disease activity index for lupus patients. The Committee on Prognosis Studies in SLE.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Data Mining in Genomics & Proteomics

Author(s): Bombardier C, Gladman DD, Urowitz MB, Caron D, Chang CH

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Abstract OBJECTIVE: To standardize outcome measures in systemic lupus erythematosus (SLE). Three indices were identified which could adequately describe outcome (disease activity, damage from disease, and health status); we describe here the development of the Disease Activity Index. METHODS: Twenty-four variables were identified as important factors in a disease activity index. These were used to generate 574 patient profiles, which were rated on a disease activity scale of 0-10 by 14 rheumatologists. A second rating of 10 of the profiles yielded scores that were not significantly different from the first, indicating that experienced clinicians can reliably make global estimates of disease activity. Multiple regression models were used to estimate the relative importance of the 24 clinical variables in the physicians' global rating of disease activity. These were estimated on a "training set" of 75\% of physicians' ratings, and then validated on a "testing set," consisting of the remaining 25\% of physicians' ratings. RESULTS: The explanatory power of the models in the training set was high (R2 = 0.93). The models' regression coefficients for the organ systems were simplified for easier use in clinical practice. This generated a "weighted" index of 9 organ systems for disease activity in SLE, the SLEDAI, as follows: 8 for central nervous system and vascular, 4 for renal and musculoskeletal, 2 for serosal, dermal, immunologic, and 1 for constitutional and hematologic. The maximum theoretical score is 105, but in practice, few patients have scores greater than 45. The SLEDAI predicted well the physicians' ratings in the testing set (Pearson's correlation coefficients = 0.64-0.79). CONCLUSION: The SLEDAI is a validated model of experienced clinicians' global assessments of disease activity in lupus. It represents the consensus of a group of experts in the field of lupus research.
This article was published in Arthritis Rheum and referenced in Journal of Data Mining in Genomics & Proteomics

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